What's the red dot?

Note: I’m having trouble publishing new posts at WUWT, so since it has been awhile since I posted at CA, I thought I’d share this puzzle with CA readers while I wait for the issue to be resolved. – Anthony

A simple question; what is that red dot on the map? I was looking at the CONUS map browser depicting the 2008 temperature departure from normal provided by NOAA’s High Plains Regional Climate Center and noticed something odd:

Click for a larger image

Note the red dot in Arizona, which is the only one in the USA. Truly an anomaly. At first I thought it might be University of Arizona Tucson and its famous parking lot station, but that is further southeast.

The other map depiction HPRCC offers also shows it, and narrows it to a single data point:

Click for a larger image

HPRCC allows us to zoom in to the regional level to get a better handle on the location:

Unfortunately, I have not found any tools on the HPRCC website that will identify this station ID. I can narrow down the location to Pinal County Arizona, and using some crude graphical tools I can approximate the lat/lon of the red dot to be : 32.9, -111.4. This puts it near the town of Florence, AZ.

Doing a search in NCDC’s MMS database for all stations in Pinal county, I find that there is indeed a COOP station #23027 in Florence, and more importantly, it is part of the “A” sub-network, which makes it a climate reporting station.

According the NCDC MMS database the lat lon for Florence COOP station is 33.0363,-111.388 so it is not very far away from my crude lat/lon estimate as seen in this Google Earth view:

Further searching the NCDC MMS database tells me that the station is “current” and that the station has an MMTS temperature unit equipped with a newer NIMBUS LCD display, and a standard rain gauge.

Using the Location tab of the NCDC MMS database I find the station is located at:

Location Description: 1206 MAIN STREET WITHIN AND 0.1 MI NW OF PO AT FLORENCE, AZ

Prior to that it was located at: 1707 S WILLOW ST, WITHIN AND 0.4 MI SW OF PO AT FLORENCE, AZ

So, I put that address into Google Web Search and found this in the FCC database for a tower registration:

So it appears the location is some city owned property, which makes sense, since COOP stations are often located at places that are staffed 24/7 (so somebody can take a reading once a day) and many city offices are. The lat/lon is fairly close to what the COOP coordinates are, but not quite close enough. The street address is about a half mile south of the lat/lon listed in the NCDC database:

The new location is at about 500 Main Street, rather than the 1206 Main Street listed in the NCDC MMS database. Perhaps it has been moved to a new location and NCDC has not caught up with the street address change. Perhaps the lat/lon is off. Anything is possible as I and the surfacestation volunteers constantly find discrepancies and errors in the database.

So I decided to use the new Google Street Level View feature to snoop around a bit at the two locations. I found nothing at 1206 S. Main Street except a lot of grass and buildings. It looks like perhaps a community college:

Click for an interactive view from Google Maps

But when I went looking around 500 Main Street – BINGO! I can spot both the MMTS sensor unit and the standard rain gauge to the west of the street:

Click for an interactive view from Google Maps

Looking at an aerial view using NCDC’s most current coordinates of 33.0363,-111.388 and Microsoft Live Search Maps, we can see what surrounds the sensor:

You can just barely make out the MMTS in the aerial view. In the street level view, it looks as if some crushed rock has been laid down near the sensor and it is fairly fresh. But more importantly, look at what surrounds the sensor:

Main Street with it’s traffic.

Buildings North, South, and West within about 10-30 yards

Parking lots West and East. The one East has quite an albedo. In the Arizona sun I’m sure it gets quite toasty in full sun.

It is possible this station was recently moved from the south Main Street location to the North Main Street location, which may be a warmer location, I don’t know for certain because I can’t locate any imagery of the sensor at 1206 South Main Street. Further research is needed to pin that down.

This is neither a USHCN station nor a GISS station. It is also not the only possibility for the station that produced the red dot in the HPRCC map

There is another nearby COOP “A” sub-network station at the Casa Grande National Monument run by the US Park Service, COOP station #21314:

Its lat/lon of 32.9947,-111.5367 is also close to my original crude estimate of 32.9, -111.4

You can see the red dot is question and it’s nearest neighbor here in this closeup of the HPRCC southwest US dot map:

When I plot both stations in Google Earth and compare to the HPRCC map above, it appears that the yellow dot lines up with Casa Grande, AZ and the red dot lines up with Florence, AZ. My original lat/lon estimate is the white marker:

Click for a larger image

The Casa Grande COOP station also has some interesting issues that could be responsible for a temperature rise there. Comparing aerial images on the Google Earth and Microsoft Live Search maps, which are taken at different times by different vendors, show us that it appears the parking lot for the visitor center has recently been resurfaced:

Since I have no time reference for the photos, it is also entirely possible that I have the sequence reversed and the parking lot has faded with time. But since I don’t see any significant vegetation changes nor other changes in the landscape between the two photos, and since fading usually takes a couple of years, I’m betting that we are seeing a resurface job, which can appear in a couple of days. I would expect more differences in vegetation or other changes if the pictures were taken years apart.

I think I can make out the Cotton region Shelter on the Google Earth image, just south of the visitor center. There is a street level view of the visitor center parking lot, which you can examine for yourself, but there are no weather instruments visible.

But there is another twist, according to the NCDC database, the station has recently been converted from a Cotton Region Shelter with max-min thermometers to the MMTS system, with the CRS maintained as backup instrument, So the MMTS may be closer to the building and/or the parking lot:

Click for a larger image

But on 10-18-2007 it appears the CRS was removed as a backup instrument. The picture above may be the only photographic record of it’s placement. As we have seen time and time again, the MMTS often gets closer to buildings due to trenching issues and cabling, so it may have introduced a bias in this station due to the placement change. It may not, I don’t know for certain since I can’t spot the MMTS at Casa Grande.

I also thought perhaps there may be a large amount of missing data in the observer B91 forms that could account for the anomaly. I checked both Florence and Casa Grande B91 observer forms at NCDC and they both appear current and well populated with data in the last year, you can search for B91 forms yourself here:

So we have two possible candidates for the station that made the red dot. Both have potential placement issues. It makes you wonder how many more of the dots in the HPRCC map have issue like this. I only spotted this one because it was such a large singular anomaly. I’ll check with HPRCC on Monday to see if they can identify the dot’s data origin for me. In the meantime I need help from our readers and volunteers.

Can anyone living in Arizona get photographs of these stations for me?

aside from the obvious such as why these sites are being moved and nothing in the data would indicate these changes, i wonder if there are any readers or people locally who could confirm. i would think maybe just a phone call to this last complex and asking if any resurfacing was done could maybe clear it up.

just as an afterthough, admittedly i’m not familiar, has any objective study been done to see what the average temperature increases are when sensor are placed near these buildings, parking lots or busy roads? maybe it could be adjusted for in the data? obviously would be very hard to construct…

any point of contact or submission you would like if people do take some time to look at the other sensors? seems like some of the others like western north dakota or colorado should be looked at…

Hmm. I notice that not only has the parking lot got darker in the lower Casa Grande photo, but the terrain around it has also turned slightly red. It looks like the Microsoft Maps picture was shot with a blue filter. No resurfacing, in my opinion.

…which is the end of the road leading up to the Casa Grande visitor center, you will see that the main road appears grey and that the black asphalt ends at the junction. Note the junction has some smear marks, possibly from fresh tar. This implies a contracted asphalt job only for the Park Service location.

I live in Central Va (Culpeper County). Are there any stations that need to be surveyed in that area? I’d like to take my son on a field trip to help explain the problem with GW “data” and the “concensus” it forms.

The resurfaced appearance could be a photographic anomaly or could simple be the result of a rainstorm washing the dirt of the road.

I doubt an actual resurfacing since both pictures show discoloration in specific spots. For example, the top row of parking spaces third from the left. Or the hemispherical shape on the bottom row near the access road. These discoloration look like part of the road surface and would have been lost if it really was resurfaced

The USHCN description only lists the USHCN stations as being the primary stations, with other observer network stations being used to adjust those. But it is supposed to be the USHCN station where the data comes from (which is adjusted using the surrounding stations), then they do all of the geographical distribution from there.
Anyways, I looked at the remarks tab for Casa Grande and it says the CRS was removed in october of 07.

The discolorations are wind blown and human trafficked sand and gravel I think. Winds tend to drop sand and small particles in response to a wind break, and it this case it is the building. People’s shoes and vehicle treads also tend to drop sand and gravel, and this being a visitor center, it does get high traffic. The other discoloration is because (IMHO) the road that runs south (W. Ruins Road) is packed sand and/or gravel, and that would obviously get tracked into the parking lot with traffic.

Most likely the patterns would be the same for both photos since traffic and wind drift patterns, once established, usually don’t change unless the land use or buildings/grounds/paths change.

It would appear that there was a site change in April of ’08 that added some UHI like effect to the low temperature. The —-z means that there was not data for that month. That there is an annual average for the year with that much data missing could also be a contributor to the red blot.

There are also several trees removed from the brown sand image, north of the parking lot to between the two diagonally sited buildings. I’d be fairly sure that the brown sand image was taken before the grey sand image. It could have been some time before as the remaining bushes have become larger.

Quick tip. Copy each image to an image program. Select one, invert its colour, make it 50% transparent. Copy and paste it on top of the first image and fiddle with the handles to make the sizes exact to one pixel. It’s a bit like putting a semi transparent photo neg over its printed positive. The expected uniform colour of the blend will show different colours where something has changed on either neg or pos. The missing trees hit the eye as pale grey blobs. The kerb line on the SE of the parking lot might have been realigned a meter or so as well, as this method shows, from the big tree at the se corner of the lot to the exit road. Finally, some wall-like structures appear on the grey earth image, running N-S, at the west end of the parking lot.

There is doubt about the resufacing proposition because the painted lane lines align very closely before and after. But, if they were originally low concrete separators, this could explain that.

Re: bugs (#21), If you want a cherry to pick, figure out what that green spot is east of Lake Havasu City AZ. The dark green spot that is in sea of yellow and orange. Hard to believe that one spot would be cooling while the rest of the entire state is warming, unless there is some sort of error in the measurement or collection. Errors are errors, either hot or cold. Perhaps that green spot is the only one in the state without a UHI effect.

In my work, we look for those cases and study those in detail. This is done to spot weaknesses that might be present in other situations, but in smaller magnitude. We actually love those special cases. Identifying the bug might give us a better product.
(Sorry for non-native english).

Bugs,
I’ll assume that you are merely ignorant and are not being intentionally misleading. Go over to Anthony’s blog and you will find that he has documented many, many surface temperature recording sites that have similar problems. Once you have educated yourself on the subject come on back and we can discuss it.

It isn’t “an interesting case of cherry picking” so much as it is noticing a map that shows a warm anomaly in a particular area of the country. When it is “drilled into” there appears to be a single station that is reporting an average temperature six to eight degrees warmer than all the surrounding stations. This single data point is used to “warm” an rather large area on the map. The larger question it raises is one of competence of the entity producing the data display. Why didn’t anyone at NOAA say “hmm, let me look at that warm spot” and notice that it was a single station reporting a +6 to 8 degree anomaly when other stations nearby are reporting 0 to 2. If you have a half-dozen stations within 100 miles showing no or low deviation from “average” and one single data source reporting 6 to 8 degrees deviation, a responsible reaction is to flag that source for inspection and remove that source from the data set until it can be verified as being accurate.

The entire issue is one of quality control. Apparently nobody at NOAA looked into what is a very obvious outlier to discover why there was one red spot on the entire US map. That brings the quality of the entire product into question.

If you were a car dealer and a car arrived from the manufacturer without doors on it, wouldn’t that cause you to be wary of the overall quality control of the manufacturer? Sure, it was only one car so they could respond that you are “cherry picking” but that doesn’t change the fact that what appears to be a very obvious error slipped through the system.

But it is really even worse than that because past experience shows that had it been a NEGATIVE anomaly of 6 to 8 degrees, they probably would have flagged that data source as cold errors seem to result in action while warm errors apparently don’t.

“Bugs,
I’ll assume that you are merely ignorant and are not being intentionally misleading. Go over to Anthony’s blog and you will find that he has documented many, many surface temperature recording sites that have similar problems. Once you have educated yourself on the subject come on back and we can discuss it.”

If the problem is bad, then why is there one point standing out. If you are correct, then there would be vast sea of red on that map.

Re: bugs (#31), You are assuming that the other dots are correct just because they are ‘normal’. It is possible (I would say likely) that many of the others are reading higher than they should and only look normal because of erroneous readings.

Looking at this map you will notice a cluster of three stations near the Utah/Idaho boundary. The Northern most station shows a positive 3 to 4 degree anomaly. Oddly, that station doesn’t cause a big red splotch on the area map.

Re #20 Eric, sorry, I had not thoroughly read your post #20. Looks like you spotted the Florence oddity early.

My guess is that the problem began in mid-March, around the 14’th, which is also the time of a three-day recording gap in data. Prior to March 14 it looks like the dirunal range was maybe 30F and after the 14’th it’s closer to 20F. That’s from eyeballing data – I’ll graph the diurnal range in the morning.

I looked at some information from Morris MN, about 100 miles from Fargo, while a small outpost of the University of Minnesota is located. The online data shows a remarkable highest mean temperature of 52 deg C 🙂 one day in June 2008.

Steve Mc, this really is a strange data report. Seems to me they measured F and reporter C. Then in the graph seems to be ok, a max of 28 C but on the table there is the amazing 53 deg.C recorded on June 2. Strange, very srange indeed. Regards from the montains of Switzerland, still freezing my *** off, Freddie

That kind of thing seems to happen surprisingly often. Only today I was checking the University of Köln metereology site, which has some nice synoptic maps at http://www.meteo.uni-koeln.de/meteo.php?show=En_We_Wk, and noticed that a bunch of stations in Bosnia were reporting 26-32 degrees centigrade. Now that would be about what you would expect in June in that area, but definitely not in January, especially since adjoining stations were reporting freezing temperatures. The obvious explanation is that the reports are actually in Fahrenheit, but why would a number of stations in the Balkan mountains suddenly report in Fahrenheit? Are the reports from NATO peace-keeping forces, or coming by way of an american reporting centre or…?

Looking at the oddity in #40 pointed out by David Smith, this reminds me of an issue with the MMTS. Wasps, Bees, and other nest building insects seem to like this unit for a base of operations. The MMTS is often aptly referred to as “the beehive” for its looks:

MMTS: One of the interesting things that happened to me was at 2 different National Ruins sites I went to check an MMTS sensor. At one site there were bees coming out of the Sensor as I approached. I did not have spray in the truck that day so I went inside to borrow some and before they found it another person came along and said “You can’t kill the bees”. So they had to contact their headquarters and get a smoke team in to put the bees to sleep (or whatever it does) and then they took the sensor apart and cleaned it out. The other site there were only a few bees and I sprayed them and when I took the sensor apart half the metal sensor was covered by a mud nest. Another time we pulled a post and sensor from a site and put it in the truck and when we went to get it out bees started pouring out of the sensor so we sprayed. Luckily we no longer had our open 8 seet van or the whole inside might have been filled with angry bees.

You may not know this but bees have a hive temperature control system:

Honey Bees are cold blooded and lack auto control of their body temperature. The worker bees work hard to keep the hive at a constant temperature of about 93 degrees Fahrenheit. To heat the hive the workers contract flight muscles without moving their wings. To cool the hive they pump their abdominal system to move air through their spiracles and trabecules to evaporate the water.

It’s that time of year that wasps, yellow jackets, and dirtdobbers build their nests inside the MMTS outside unit, as well as under the F/P Rain gage. All observers should be careful when mowing or cleaning in and around these two pieces of equipment.

Since there apparently is no “bee correction factor” for temperature data, one wonders how much of the climate record is buggy. Obviously the problem will go undetected for awhile before the observer or COOP manager finds and fixes the infestation. With thousand of these units in the USA, I would think that spring bee season may have an impact on the record.

I don’t recall ever hearing about bees swarming around mercury thermometers in Stevenson Screens – too much wide open space in there. We have one at the TV station I worked for for 15 years, and while we’d get wasps and bees in the satellite dish covers, we never had a single insect problem in the Stevenson Screen just 50 feet away.

Since the data issue with the Florence station was transient, started in spring, and seemed to affect the lows rather than highs, it may just be a case of bee infestation. Bees would work hard to keep that hive temperature comfortable at night.

It’s that time of year that wasps, yellow jackets, and dirtdobbers build their nests inside the MMTS outside unit, as well as under the F/P Rain gage. All observers should be careful when mowing or cleaning in and around these two pieces of equipment.

Mud-dauber wasps are a nuisance here at certain times of the year, we have to put covers on the pitot tubes on parked planes because the little buggers have the habit of building their nests in such convenient holes. Miss one of those on your pre-flight inspection and the consequences could be disasterous!

It’s not even precision work when there are no insects. Even mowing grass might be a cause of variance. Tall grass around the detector has an effect like lowering its height relative to ground, by changing air flow. Published work (below) suggests temperature is sensitive to height above ground. Out here, we also burn off annually in some areas, leaving a nice black change to albedo for some weeks. I’m not sure burnoffs are done near any sensors, but grass cutting certainly is at airfields in particular.

Determination of a screen that allows accurate measurement of temperature is very difficult. All screens by their
very presence impact on the measurement of temperature. Of the screens looked at in this study the Vector
aspirated screen appears to have the least overall impact. However it needs to be born in mind that an aspirated
screen measures an integrated vertical column of air while a non aspirated screen measure a horizontal slice of
the air.

In the situation where a strong vertical gradient of temperature exists this can result in large
discrepancies.

These conditions could not be tested in this study. Also the difference of an aspirated screen to
the small Stevenson screen will be greatest at low wind speed.

This paper is recommended reading to get a feel for the size of variance when you start changing sensor types and settings.

The real lesson it not that the data is good or bad. It was not automatically flaged for investigation
and it is not straightforward to check. So it is pretty clear no-one is actually routinely checking, talking to the troops, or chasing up missing data. If the station records were right you would expect a QA script to say have a look here. You would pick up the phone/email and talk to the nearest human. Anything you want to tell us about? Or even, we did not get anything from you this week.

Start with a Email news letter, and do a yearly re-subscription/contact to ask for station moves, and fill in any gaps. Then at less they know you acknowledge the effort they are making. Would you go out in a storm to collect readings, and post them to an organisation which has not bothered to keep up routine contact when a company which sold you a WI-FI card has no trouble remembering you for years.

Re Anthony Watts #47,
In October 2007, I did a related post here on Sensor Blackening, with several links to photos on Anthony’s SurfaceStations of MMTS units covered with mildrew spots, rust streaks, clay deposits, etc. In addition to the two photos linked at the end of the main post, see especially comments #6 and 22. The Petulama station photo linked in #22 appears to have both spiders and mudwasps in residence.

What bothers me most about this darkening is that it generally builds up gradually, providing evidence of Global Warming, but if the sensor is ever cleaned, that will show up as a discontinuity and perhaps be automatically “adjusted” out of the record. However, I doubt that gradual blacking or nesting could have caused a sudden spike like that at Florence AZ.

Anthony’s relentless data checking on his two blogs is a large part of what true science is all about. His forthcoming win of Best Science Blog is well deserved!

The periods are Feb 1 thru April 30 for both 2007 and 2008. The plot seems to show a discontinuity about mid-March, 2008, a period when the station was out of service for three consecutive days. After mid-March the range seemed to drop about 10F.

(I say “seemed” because I’ve plotted no additional data yet, and it’s always possible that what we see over these ninety-day periods are real and weather-related, though I doubt that.)

I’ll look at the max and min to see if they offer clues as to what’s up. My eyeballs tell me it’s the min temperatures which are odd. Could be instrument problems, interference with radiational cooling or an artifical heat source like ACs.

The distribution of sloppiness.
I find bugs remark wonderfully unsuspecting. As an old statistician I know that when something seems to be abnormal or stands out in a material, it’s usually an error somewhere. And the first thing you do is to search for that error. This error tells me (together with the information about the surface stations I previously have acquired) that the people responsible are sloppy. And in theory errors should zero each other out, having a normal distribution with zero mean.
But what about sloppiness with biased statisticians? They may not be deliberately biased. But if you know that the politically correct view is that the world is warming (the more the better), one might have a tendency to find errors that stand in the way of confirming their preconceived opinion.
And when you do not spot an error that stands out in red – what about all the other errors?
The risk is that this kind of sloppiness does not have a normal distributed with zero mean – it’s likely to be biased. If I had been the boss of NCDC, I had been really worried.

While we’re raising Arizona, here’s a plot for Tombstone which I’ve been pondering:

In 1968/69 there was a rather sudden shift upwards in minimum temperature and a reduction in diurnal range, resembling step changes (“A”). I’ve seen similar apparent step changes in minimum temperatures at other Arizona stations, but in different decades. Odd.

I looked at the max minus min for Florence AZ, and it is clear that it has gone from 35°F in previous decades to about 21°, with a sharp dropoff lately… See chart on sheet linked below, and also see the high and low tabs. You will see highs staying steady, and lows increasing dramatically lately, leading to an overall increase of average temperature, and a severe drop in Max-Min. I presume this is due to irrigation (crops or lawns) but can’t be sure. I wish I could find humidity data because I’m willing to bet it is much higher there now than in the past.

Another plot from my dead-files shows Tombstone and Fort Valley, AZ. Both are rated as CRN 2 sites in Anthony’s SurfaceStations survey, which are pretty good ratings, but of course those ratings are current snapshots and may not properly represent historical conditions –

The apparent step changes in Tmin are odd. Tombstone was about 1968 and Fort Valley was about 1977 (around the Great Climate Shift of the late 1970s).

Also odd is the apparent swing down and then up at transition time.

I don’t rule out natural causes, or a data manipulation error on my part, or a data quality problem, or a station siting/contamination problem. I thought about the possibilities for awhile and then set them aside after getting nowhere.

Another interesting fact on my sheet… Note that the “ANN” (annual) temperatures, if present, are calculated from the average of any years’ monthly data, whether complete or not. For instance, in 2008 there are 4 missing months, yet the fact that they are missing is not compensated for in any way, i.e, not “filled in” with averages from previous years or anything, it is just the average of the months present, which happens to be missing 4 cold months. Guess what that does? It makes a red dot, I think.

Note, I did not change any values on my sheet, I simply replaced “—–” (missing data) and 9999 (missing data) with =na() so I could chart it easier. The averages you see are directly from the source http://www.wrcc.dri.edu/cgi-bin/cliMAIN.pl?az3027

Hopefully this information is “corrected”, but not “homogenized” too much before being used for anything…

There appears to be resurfacing activity in the parking lot of the buildings just east (assuming up on the photo is north) of the intersection you mentioned in the post. Same is true of the parking lot in the large building to the southeast of the intersection at 1431 N Ariz. Blvd. The visual differences between in the pavement in these two locations leads me to believe your hypothesis re new pavemment at Casa Grande is correct.

Note that in photo #8 in Anthony’s post, the buildings to the N of the MMTS and across the street to the E both have silvery aluminized or galvanized roofs. Their high albedo is both budget- and eco-friendly, as it reduces the need for A/C while it alleviates UHI and makes the city cooler for neighbors.

However, this material may cast an almost spectral reflection of the sun. The building to the S of the MMTS at 500 N Main in the somewhat dated photo #7 is shown with shake or mock-shake asphalt shingles that have lower albedo, but that would cast no reflection. If this building had its roofing changed in say March of 2008 to the same sensible material as its neighbors, and it happened to cast a reflection of the sun on the MMTS, this might have greatly altered the temperature readings there.

The data have not been adjusted for station relocations, heat island effects, instrument changes, or time of observation biases. The nature of inhomogeneities arising from such factors depends on a station’s climatic regime.

So, I assume it is “raw”, which is what I’d intend to use for the current purposes of looking for problems with siting, bees, instruments, etc.

But, having said that, I’m not always sure what is raw and what has been adjusted. I sometimes trip myself with this data and try to be extra cautious.

Here’s an oddity which adds to my trepidation. The October 1914 USHCN printout for Tombstone gives these daily values (I circled relevant data for October 1):

Now, the original handwritten form happens to be available for Tombstone. The photocopy is hard to read but perhaps enough will be visible here. Agaian, I’ve circled relevant values:

Fortunately, the handwritten page is averaged at the bottom and gives October, 1914 as 62.85F. The USHCN printout gives October, 1914 as a degree cooler at 61.8F.

(The original form can be viewed via this link with some maneuvering. It may require registration.)

Is the USHCN daily data I’m using somehow adjusted? Dunno. If so, it’s an odd and random daily adjustment.

Is this an isolated incident? Dunno. I spot-checked recent records and they match. Maybe this is a historical issue or simply transcription errors. That may be a topic worth some exploration.

Thanks, now I have a better idea of what I’m looking at. Seems to be a lot of “scribal” errors if what I’m seeing on the form is what is supposed to be in the file. It looks like the form says 85, 85, 69, 71, 74 for the highs but the file says 88,88, 65, 70, 74? Similarly the lows are 61, 61, 54, 42, 50 and the file 60, 58, 46, 49, 51. If the readme file isn’t telling you about adjustments that are above and beyond the ones listed as not being there there are an awful lot of transcription errors.

Those doubting the value of noting the red spot would be advised to read how the Hubble telescope came to have the wrong curvature on its mirror. It was an elementary arithmetic mistake, not detected by quality control. http://adsabs.harvard.edu/abs/1990STIN…9112437.

Now, for penance, try to estimate the extra GHG put into the atmosphere in correcting the Hubble optics.

Those doubting the value of noting the red spot would be advised to read how the Hubble telescope came to have the wrong curvature on its mirror.

I worked on the Hubble program at Lockheed [now Lockheed Martin]. The cited article is one in a long series of [very successful] spin control reports.

What actually happened was that the Hubble’s secondary mirror, about the size of a nickel, had been ground and polished on both sides. The proper side had the correct curvature; the reverse side was ground and polished to make it pretty, because it had cost the taxpayers a pretty penny. But it did not have the correct curvature. The secondary mirror was then installed backward by mistake, and the shuttle was launched.

The primary mirror had been constantly checked and re-checked for accuracy; the little secondary mirror was more or less taken for granted, and assumed to be accurate. It looked very similar on both sides. The focal length of the telescope was such that a real world test could not be done except from orbit.

Blame for the primary mirror’s flawed grinding was immediately laid on Perkin Elmer corp., although the primary mirror had been correctly fabricated. The ostensible ‘fix’ was to replace the secondary mirror with a new one corrected for the [non-existent] primary flaw, and a shuttle mission was launched with much fanfare to replace the secondary mirror. The fix was successful.

Perkin Elmer went along with the scenario, and interestingly, Perkin Elmer stock immediately began a substantial rise. If someone were a conspiracy theorist, they might think that Perkin Elmer had been paid off by Lockheed to take the fall.

I’m not trying to rag on Lockheed Martin, which is a good company. But there is intense competition among aerospace/defense contractors for lucrative government contracts, and companies will go to great lengths to maintain their public image.

The secondary mirror was then installed backward by mistake, and the shuttle was launched.

It seems rather improbable that the reverse of the secondary (0.3 m diameter – not a nickel for my pockets) would accidentally have almost the correct shape. Also AFAIK polishing a mirror “to make it pretty” is way below the standards it must have had to produce the images observed before the correction – and there is the problem of coating. The story doesn’t look convincing to me.

Re: Kusigrosz (#75), I seem to recall a definitive explanation in Popular Science several years ago that attributed the fuzzy focus to a cap placed on the wrong end of a measuring rod used when the telescope was assembled. This is very vague in my memory, but I think the cap was rounded inside and was supposed to be placed over the end of the rod that was similarly rounded, but instead was placed over the other end, which was flat. The measuring rod was thus longer than it should have been, with the result that the distance within the structure that it was used to measure was too great.

So either Perkin Elmer sabotaged the the reflective null corrector (RNC) used during polishing of the primary mirror, which the Hubble Space Telescope Optical Systems Board of Investigation examined and found to be both defective and a fully satisfactory explanation of the observed problem, or the board conspired with both Lockheed and Perkin Elmer to stitch up Perkin Elmer? Seems a tad far-fetched.

RE #74-#76, whatever the problem with the Hubble telescope, the Investigatory Board report originally cited by Geoff Sherrington in #72 concluded,

This methodology should have alerted NASA management to the fragility of the process and the possibility of gross error. Such errors had been seen in other telescope programs, yet no independent tests were planned, although some simple tests to protect against major error were considered and rejected.

This brings to mind some other instances in which NASA management has continued to overlook the possibility of gross error, and has made insufficient tests to protect against it …

This brings to mind some other instances in which NASA management has continued to overlook the possibility of gross error, and has made insufficient tests to protect against it …

When government sponsored enterprises/agencies like NASA can shift the blame and responsibility to their vendors without facing much in the way of adverse repercussions, I really think that process becomes part of their thinking and unfortunately part of their project planning or lack thereof. I doubt that NASA’s attitude is unique among government sponsored enterprises as evidenced by the recent financial crisis.

While I enjoy reading these anecdotal accounts of the temperature measuring stations and value the importance of them in directing interest to recording the current quality control with the goal of improving it, I also see a need for more comprehensive analysis of the station data. A more detailed and extensive treatment of the Watts’ team CRN quality ratings of stations, when work is completed or approaches completion, is what I hope we see some day soon.

In the meantime, I have made some station by station temperature trend comparisons of the USHCN temperature series of Version 2, Urban adjusted and Filenet. Version 2 is a later version of the Urban adjusted series and a comparison there allows one to obtain a measure of the uncertainties involved in the rather extensive adjustments that are made as one progresses from the raw to final adjusted series. I also made a station by station temperature trend comparison of these USHCN series to the GISS temperature series with the final GISS homogeneity adjustment.

I had prepared a lengthy commentary that included some introductory and background information and attempted to post it on the Tucson thread. All, my attempts with the complete and abridged versions were spammed out of existence. As I was hearing a high pitched voice shouting spam, spam, spam at me, I had further thoughts on the posting matter and decided to simply present the results and determine from there whether there is any interest in discussing these issues further. On additional consideration, I decide it might be better to pose the question here whether there might be any interest in posting these analysis results on this thread. Below is an outline of my analyses/comparisons:

The comparisons were made using annual average temperature trends for individual stations in two data series being compared and analyzing the statistics of matched samples that were differenced for each individual station temperature trend over the time periods indicated (1895-2006 and 1955-2006).

The statistics, for which the results are reported below, were as follows:

1. The average difference in temperature trends between the two data series over the stations included in the analysis.
2. The standard deviation of the trend differences.
3. The number of stations used in the analysis
4. The standard error of the mean (SEM).
5. The t statistic derived using the average temperature trend difference and the SEM to determine the probability that the difference between the data series occurred by chance.

In anticipation of an overwhelming demand, I have gone ahead with the posting of the analysis results (without discussion) as discussed above.

The analysis below was station by station temperature trend differences in degrees C per century where n is equal to the number of stations in the analysis. Only stations with complete annual data were used in the USHCN intra version comparisons. The USHCN versions to GISS comparison were made for individual stations with missing years’ data but all comparisons used the same years’ data, i.e. if a year was missing for GISS, that USHCN year was not used.

I have almost finished a compilation of temperatures from some Australian Reference Rural Stations and am cogitating on how to present it. At first blush the results can be described in a page or so, but then many readers would ask whatifs. In looking at your post #84, I have lots of supplementary questions because I’m in Australia and we do not commonly even use the abbreviations that you have.

The Bureau here has told me that it has no control over what happens to the data it generates here and passes on for global calculations. Therefore, I do not even know if some of the Aust data are adjusted twice or not at all. Certainly, some of the raw data has shown virtually no change in the last 40 years and that raises a big question in itself, because by the time it’s been purified to USA standards it seems to have gained some flavour.

I wonder if Steve would mind you expanding your description (maybe on the message board) so that it is a little less cryptic. Thanks to Climate Audit and past reading I can work through it, but without the confidence it deserves. What is your most significant conclusion?

The difference of 0.201 plus/minus 0.062 degrees C per century for the period 1955-2006 was larger than I would have expected particularly when the difference is for the same USHCN series using two different approaches – and approaches that should affect more or less exclusively the urban or UHI effects. I frequently see these differences quoted for the longer term trends and as the results below show that difference can be significantly smaller than the trends over a more recent time period. One could obtain the false impression that the long term differences quoted could be applied for shorter time intervals within the entire range.

2. USHCN Urban versus USHCN Filenet

The results for this comparison shows the surprising effect that the USHCN Urban minus the USHCN Filenet trend differences indicate that for the 1895-2006 time period the urban adjustment was essentially zero. Again, as in the above cited case, when one looks at a more recent time period, the adjustment shows the more expected trend difference of 0.175 plus/minus 0.08 degrees C per century. Also the relatively large standard deviations should be noted for both this case and that for the Version 2 versus Urban comparison from above, indicating that while the individual station adjustments can be relatively quite large they tend to “average out”.

3. GISS adjusted for homogeneity versus USHCN Version 2

The third observation of the results involves a look at two different sources of temperature sets and shows that GISS trends tend to run cooler than the USHCN counterpart by 0.2 to 0.3 degrees C per century – although with the smaller sample sizes here the t test would indicate that the differences are borderline statistically significant. This difference between GISS and USHCN is acknowledged by the authors of these two data series but their difference is based on the GISS versus USHCN Urban comparison (see discussion below).

4. GISS adjusted for homogeneity versus USHCN Urban

In this comparison, for the sample analyzed, I saw no difference between the average station differences for both time periods observed.

5. GISS adjusted for homogeneity versus Filenet
In this comparison the results show that the average trend differences for the stations with brightness = 0 meets the expectation of being essentially 0 and the expectation of the standard deviation of the differences being significantly smaller than that for the station differences where the brightness levels were greater than zero (by way of F tests).

Regressing and plotting the station trend differences between GISS and Filenet against the GISS satellite brightness levels, for those stations with a level greater than 0, one would expect that there should be a positive trend. Although for the 1895-2006 period one can see a positive trend on the graphs for both comparisons, the trends cannot be shown to be statistically different than zero.

In conclusion, I found the analysis, using trend differences between individual stations for temperature series comparisons, reveals some puzzling results that are not evident with the more commonly used comparisons. I also find, in the same vain as Steve M has previously commented on here at CA, that the GISS data being available for single station downloads makes the comparison task more difficult.

GISS appears to concentrate their efforts on obtaining regional and global, as opposed to local, temperature anomalies in grid form and puts more emphasis on that process than attempting to look at and analyze individual station data. The most puzzling aspect of this analysis was how the rural stations are designated and than used to control the near proximity more urban stations. This would seem to put critical emphasis on the micro site quality of rural stations, but as the Watts team CRN ratings show that does not appear to be the case that often. It also would appear to require a good correlation between the nearby rural station temperature trends and that of the urban stations trends that would have existed without any UHI and micro site effects. That condition, in my view, places some unacknowledged and perhaps unknowable uncertainties in these adjustments.

Re #80, Kenneth Fritsch: I am sure that Steve McIntyre would be delighted to give you your own thread to present this material in its entirety, and to facilitate discussion. My impression is that you stand out as one of the most genuinely scientific and professional contributors here at CA, and many of us would very much appreciate seeing your work.

Thanks for the comment, Trevor, but I personally do not judge my expertise on these subject matters at the level of those who post threads here and would prefer that Steve M maintain his current criteria level.

I post here sometimes hoping to steer a discussion into another direction. I simply hope that my efforts are with all due respect to the preferences of the host and other posters here.

I live an hour or so away from the Florence site at the top of the thread. If anyone would like me to make a visit and perhaps ask any locals about what changes have taken place in the area, let me know. I haven’t been involved in this stuff before, so I’m not sure of the protocol of what should be done to check this out.

Re: narby (#86),
narby, it’d be great if you could make a trip to Florence. Here’s a link to Anthony’s instructions for surveying sites, if you choose to do a SurfaceStations-quality check. It’s a good primer even if you don’t want to do the formal survey. Be sure to check for bees and spiders 🙂

The question I wish you’d ask is, “There were no temperatures recorded for three consecutive days in mid-March, 2008. Was that outage for a change to the MMTS (relocation, repair, etc)?”

OK, so we can admit that putting a temp detection device in the middle of a concrete parking lot will make it read higher temperatures but we can’t admit that paving over vast swaths of land will increase the overall temperature of the planet? I see nothing wrong with the placement of the device. Wouldn’t it be just as misleading to place every one in the middle of a vast grassy meadow, don’t see many of them in Arizona nowadays.

I just had to comment that I like David Smith’s approach to analyzing the red dot anomaly in an attempt to resolve what might have caused the red dot.

I do have some questions about what the temperature anomaly with the red dot represents. The map is labeled provisional and does that mean it is subject to some yet to be performed quality control and/or adjustments? How, if at all, would these measurements affect the USHCN and/or the GISS temperature series?

I could not find Florence, AZ listed as an USHCN station – with the closest station to the coordinates being Sacaton, AZ at 33.07 and -111.75.

I have a general question about the point in time when the owners of a temperature series should know that temperatures recorded have issues. Version 2 of the USHCN series uses a change point algorithm to check for suspicious temperatures recorded and evidently will use that algorithm exclusively for finding suspect recordings as well as other non-climate effects such as UHI. Change points would be difficult to resolve within a year or so time frame and would not efficiently find errors until sometime well into the future. I would hope that when updated temperature series are published that the provisional nature of the underlying recorded temperatures is prominently displayed and explained in some detail. I think that would be the point of drawing attention to these anecdotal larger-than-expected anomalies – isn’t it?

[…] Another fellow blogger placed an interesting blog post on What's the red dot? Â« Climate AuditHere’s a brief overviewThe USHCN description only lists the USHCN stations as being the primary stations, with other observer network stations being used to adjust those. But it is supposed to be the USHCN station where the data comes from (which is adjusted … […]